Machine Learning software that predicts annual CO2 emissions from base stations around the World

I developed Machine Learning software that predicts annual CO2 emissions from base stations around the world. With this machine learning software, you will be able to predict how much CO2 is emitted by base stations in which country, year by year. You will also be able to find the predicted country. The decision tree is automatically saved as .dot. The data has been meticulously entered by me and the software is completely original.

The values you enter should be (respectively):

1) Estimated annual CO2 emissions (in kilotons) from diesel generators in mobile towers, predict for 2014

2) Estimated annual CO2 emissions (in kilotons) from diesel generators in mobile towers, predict for 2020

3) Enter population

Example: model_run = model.predict([[int(predict_2014),int(predict_2020),int(predict_population)]])

Outpot : Predicted country: ['Latin America']

I am happy to present this software to you!

Data Source: https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2020/09/Clean_Tech_Report_R_WebSingles.2.pdf https://www.worldometers.info/world-population/south-eastern-asia-population/[DataSource1] https://www.worldometers.info/world-population/[DataSource2] https://www.statista.com/statistics/805605/total-population-sub-saharan-africa/[DataSource3] ###The coding language used:

Python 3.9.6

###Libraries Used:

Sklearn

Pandas

Developer Information:

Name-Surname: Emirhan BULUT

Contact (Email) : emirhan.bulut@turkiyeyapayzeka.com

LinkedIn : https://www.linkedin.com/in/artificialintelligencebulut/

Official Website: https://www.emirhanbulut.com.tr